A Cost Analysis Of Carbon Dioxide Emission Reduction Strategies For New Plants In Michigan's Electric Power Sector

This thesis attempts to find the least-cost strategy to reduce CO2 emission by replacing coal by other energy sources for electricity generation in the context of the proposed EPA’s regulation on CO2 emissions from existing coal-fired power plants. An ARIMA model is built to forecast coal consumption for electricity generation and its CO2 emissions in Michigan from 2016 to 2020. CO2 emission reduction costs are calculated under three emission reduction scenarios- reduction to 17%, 30% and 50% below the 2005 emission level. The impacts of Production Tax Credit (PTC) and the intermittency of renewable energy are also discussed. The results indicate that in most cases natural gas will be the best alternative to coal for electricity generation to realize CO2 reduction goals; if the PTC for wind power will continue after 2015, a natural gas and wind combination approach could be the best strategy based on the least-cost criterion.

Review of assessment, design, and mitigation of multiple hazards

Large parts of the world are subjected to one or more natural hazards, such as earthquakes, tsunamis, landslides, tropical storms (hurricanes, cyclones and typhoons), costal inundation and flooding. Virtually the entire world is at risk of man-made hazards. In recent decades, rapid population growth and economic development in hazard-prone areas have greatly increased the potential of multiple hazards to cause damage and destruction of buildings, bridges, power plants, and other infrastructure; thus posing a grave danger to the community and disruption of economic and societal activities. Although an individual hazard is significant in many parts of the United States (U.S.), in certain areas more than one hazard may pose a threat to the constructed environment. In such areas, structural design and construction practices should address multiple hazards in an integrated manner to achieve structural performance that is consistent with owner expectations and general societal objectives. The growing interest and importance of multiple-hazard engineering has been recognized recently. This has spurred the evolution of multiple-hazard risk-assessment frameworks and development of design approaches which have paved way for future research towards sustainable construction of new and improved structures and retrofitting of the existing structures. This report provides a review of literature and the current state of practice for assessment, design and mitigation of the impact of multiple hazards on structural infrastructure. It also presents an overview of future research needs related to multiple-hazard performance of constructed facilities.

Will Whole-Tree Harvest of Jack Pine (Pinus banksiana) deplete soil nutrients in low-productivity sand soils?

In 2009 and 2010 a study was conducted on the Hiawatha National Forest (HNF) to determine if whole-tree harvest (WTH) of jack pine would deplete the soil nutrients in the very coarse-textured Rubicon soil. WTH is restricted on Rubicon sand in order to preserve the soil fertility, but the increasing construction of biomass-fueled power plants is expected to increase the demand for forest biomass. The specific objectives of this study were to estimate biomass and nutrient content of above- and below-ground tree components in mature jack pine (Pinus banksiana) stands growing on a coarse-textured, low-productivity soil, determine pools of total C and N and exchangeable soil cations in Rubicon sand, and to compare the possible impacts of conventional stem-only harvest (CH) and WTH on soil nutrient pools and the implications for productivity of subsequent rotations. Four even-aged jack pine stands on Rubicon soil were studied. Allometric equations were used to estimate above-ground biomass and nutrients, and soil samples from each stand were taken for physical and chemical analysis. Results indicate that WTH will result in cation deficits in all stands, with exceptionally large Ca deficits occurring in two stands. Where a deficit does not occur, the cation surplus is small and, chemical weathering and atmospheric deposition is not anticipated to replace the removed cations. CH will result in a surplus of cations, and will likely not result in productivity declines during the first rotation. However even under CH, the surplus is small, and chemical weathering and atmospheric deposition will not supply enough cations for the second rotation.

Development of an optimization model for biofuel facility size and location and a simulation model for design of a biofuel supply chain

To mitigate greenhouse gas (GHG) emissions and reduce U.S. dependence on imported oil, the United States (U.S.) is pursuing several options to create biofuels from renewable woody biomass (hereafter referred to as “biomass”). Because of the distributed nature of biomass feedstock, the cost and complexity of biomass recovery operations has significant challenges that hinder increased biomass utilization for energy production. To facilitate the exploration of a wide variety of conditions that promise profitable biomass utilization and tapping unused forest residues, it is proposed to develop biofuel supply chain models based on optimization and simulation approaches. The biofuel supply chain is structured around four components: biofuel facility locations and sizes, biomass harvesting/forwarding, transportation, and storage. A Geographic Information System (GIS) based approach is proposed as a first step for selecting potential facility locations for biofuel production from forest biomass based on a set of evaluation criteria, such as accessibility to biomass, railway/road transportation network, water body and workforce. The development of optimization and simulation models is also proposed. The results of the models will be used to determine (1) the number, location, and size of the biofuel facilities, and (2) the amounts of biomass to be transported between the harvesting areas and the biofuel facilities over a 20-year timeframe. The multi-criteria objective is to minimize the weighted sum of the delivered feedstock cost, energy consumption, and GHG emissions simultaneously. Finally, a series of sensitivity analyses will be conducted to identify the sensitivity of the decisions, such as the optimal site selected for the biofuel facility, to changes in influential parameters, such as biomass availability and transportation fuel price. Intellectual Merit The proposed research will facilitate the exploration of a wide variety of conditions that promise profitable biomass utilization in the renewable biofuel industry. The GIS-based facility location analysis considers a series of factors which have not been considered simultaneously in previous research. Location analysis is critical to the financial success of producing biofuel. The modeling of woody biomass supply chains using both optimization and simulation, combing with the GIS-based approach as a precursor, have not been done to date. The optimization and simulation models can help to ensure the economic and environmental viability and sustainability of the entire biofuel supply chain at both the strategic design level and the operational planning level. Broader Impacts The proposed models for biorefineries can be applied to other types of manufacturing or processing operations using biomass. This is because the biomass feedstock supply chain is similar, if not the same, for biorefineries, biomass fired or co-fired power plants, or torrefaction/pelletization operations. Additionally, the research results of this research will continue to be disseminated internationally through publications in journals, such as Biomass and Bioenergy, and Renewable Energy, and presentations at conferences, such as the 2011 Industrial Engineering Research Conference. For example, part of the research work related to biofuel facility identification has been published: Zhang, Johnson and Sutherland [2011] (see Appendix A). There will also be opportunities for the Michigan Tech campus community to learn about the research through the Sustainable Future Institute.

Cladophora, mass transport, and the nearshore phosphorus shunt

Excessive Cladophora growth in the Great Lakes has led to beach fouling and the temporary closure of nuclear power plants and has been associated with avian botulism and the persistence of human pathogens. As the growth-limiting nutrient for Cladophora, phosphorus is the appropriate target for management efforts. Dreissenids (zebra and quagga mussels) have the ability to capture particulate phase phosphorus (otherwise unavailable to Cladophora) and release it in a soluble, available form. The significance of this potential nutrient source is, in part, influenced by the interplay between phosphorus flux from the mussel bed and turbulent mixing in establishing the phosphorus levels to which Cladophora is exposed. It is hypothesized that under quiescent conditions phosphorus will accumulate near the sediment-water interface, setting up vertical phosphorus gradients and favorable conditions for resource delivery to Cladophora. These gradients would be eliminated under conditions of wind mixing, reducing the significance of the dreissenid-mediated nutrient contribution. Soluble reactive phosphorus (SRP) levels were monitored over dreissenid beds (densities on the order of 350•m-2 and 3000∙m-2) at a site 8 m deep in Lake Michigan. Monitoring was based on the deployment of Modified Hesslein Samplers which collected samples for SRP analysis over a distance of 34 cm above the bottom in 2.5 cm intervals. Deployment intervals were established to capture a wind regime (calm, windy) that persisted for an interval consistent with the sampler equilibration time of 7 hours. Results indicate that increased mussel density leads to an increased concentration boundary layer; increased wind speed leads to entrainment of the concentration boundary layer; and increased duration of quiescent periods leads to an increased concentration boundary layer. This concentration boundary layer is of ecological significance and forms in the region inhabited by Cladophora

DEVELOPMENT OF AN OPTIMIZATION MODEL FOR BIOFUEL FACILITY SIZE AND LOCATION AND A SIMULATION MODEL FOR DESIGN OF A BIOFUEL SUPPLY CHAIN

A range of societal issues have been caused by fossil fuel consumption in the transportation sector in the United States (U.S.), including health related air pollution, climate change, the dependence on imported oil, and other oil related national security concerns. Biofuels production from various lignocellulosic biomass types such as wood, forest residues, and agriculture residues have the potential to replace a substantial portion of the total fossil fuel consumption. This research focuses on locating biofuel facilities and designing the biofuel supply chain to minimize the overall cost. For this purpose an integrated methodology was proposed by combining the GIS technology with simulation and optimization modeling methods. The GIS based methodology was used as a precursor for selecting biofuel facility locations by employing a series of decision factors. The resulted candidate sites for biofuel production served as inputs for simulation and optimization modeling. As a precursor to simulation or optimization modeling, the GIS-based methodology was used to preselect potential biofuel facility locations for biofuel production from forest biomass. Candidate locations were selected based on a set of evaluation criteria, including: county boundaries, a railroad transportation network, a state/federal road transportation network, water body (rivers, lakes, etc.) dispersion, city and village dispersion, a population census, biomass production, and no co-location with co-fired power plants. The simulation and optimization models were built around key supply activities including biomass harvesting/forwarding, transportation and storage. The built onsite storage served for spring breakup period where road restrictions were in place and truck transportation on certain roads was limited. Both models were evaluated using multiple performance indicators, including cost (consisting of the delivered feedstock cost, and inventory holding cost), energy consumption, and GHG emissions. The impact of energy consumption and GHG emissions were expressed in monetary terms to keep consistent with cost. Compared with the optimization model, the simulation model represents a more dynamic look at a 20-year operation by considering the impacts associated with building inventory at the biorefinery to address the limited availability of biomass feedstock during the spring breakup period. The number of trucks required per day was estimated and the inventory level all year around was tracked. Through the exchange of information across different procedures (harvesting, transportation, and biomass feedstock processing procedures), a smooth flow of biomass from harvesting areas to a biofuel facility was implemented. The optimization model was developed to address issues related to locating multiple biofuel facilities simultaneously. The size of the potential biofuel facility is set up with an upper bound of 50 MGY and a lower bound of 30 MGY. The optimization model is a static, Mathematical Programming Language (MPL)-based application which allows for sensitivity analysis by changing inputs to evaluate different scenarios. It was found that annual biofuel demand and biomass availability impacts the optimal results of biofuel facility locations and sizes.